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Tag: SARS-CoV-2

  • Maternal mRNA COVID-19 vaccination shields infants for six months

    Maternal mRNA COVID-19 vaccination shields infants for six months

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    Women who receive an mRNA-based COVID-19 vaccination or booster during pregnancy can provide their infants with strong protection against symptomatic COVID-19 infection for at least six months after birth, according to a study from the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health. These findings, published in Pediatrics, reinforce the importance of receiving both a COVID-19 vaccine and booster during pregnancy to ensure that infants are born with robust protection that lasts until they are old enough to be vaccinated.

    COVID-19 is especially dangerous for newborns and young infants, and even healthy infants are vulnerable to COVID-19 and are at risk for severe disease. No COVID-19 vaccines currently are available for infants under six months old. Earlier results from the Multisite Observational Maternal and Infant COVID-19 Vaccine (MOMI-Vax) study revealed that when pregnant volunteers received both doses of an mRNA COVID-19 vaccine, antibodies induced by the vaccine could be found in their newborns’ cord blood. This suggested that the infants likely had some protection against COVID-19 when they were still too young to receive a vaccine. However, researchers at the NIAID-funded Infectious Diseases Clinical Research Consortium (IDCRC), which conducted the study, did not know how long these antibody levels would last or how well the infants would actually be protected. The research team hoped to gather this information by following the infants through their first six months of life.

    In this portion of the study, researchers analyzed data from 475 infants born while their pregnant mothers were enrolled in the MOMI-Vax study. The study took place at nine sites across the United States. It included 271 infants whose mothers had received two doses of an mRNA COVID-19 vaccine during pregnancy. The remaining 204 infants in the study were born to mothers who had received both doses of an mRNA COVID-19 vaccine as well as a COVID-19 booster. To supplement data gathered during pregnancy and at birth, the infants were evaluated during at least one follow-up visit during their first six months after birth. Parents also reported whether their infants had become infected or had demonstrated COVID-19 symptoms.

    Based on blood samples from the infants, the researchers found that newborns with high antibody levels at birth also had greater protection from COVID-19 infection during their first six months. While infants of mothers who received two COVID-19 vaccine doses had a robust antibody response at birth, infants whose mothers had received an additional booster dose during pregnancy had both higher levels of antibodies at birth and greater protection from COVID-19 infection at their follow-up visits.

    While older children and adults should continue to follow guidance from the Centers for Disease Control and Prevention (CDC) to stay up-to-date on their COVID-19 vaccines and boosters, this study highlights how much maternal vaccination can benefit newborns too young to take advantage of the vaccine: During the course of this study, none of the infants examined required hospitalization for COVID-19. Researchers will continue to evaluate the data from the MOMI-Vax study for further insights concerning COVID-19 protection in infants.

    Source:

    NIH/National Institute of Allergy and Infectious Diseases

    Journal reference:

    Cardemil, C. V., et al. (2024). Maternal COVID-19 Vaccination and Prevention of Symptomatic Infection in Infants. Pediatrics. doi.org/10.1542/peds.2023-064252.

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  • Smoking, infection, and BMI found to significantly sway immune response, study shows

    Smoking, infection, and BMI found to significantly sway immune response, study shows

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    In a recent study published in the journal Nature, researchers explored the factors influencing cytokine release, a critical component of the host immunological response.

    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic emphasized the wide variation in immunological responses between populations, with age, sex, and genetic variables all playing vital roles. However, therapy and vaccine development often disregard immunological diversity. The Milieu Intérieur research project has contributed to understanding immune homeostasis by quantitatively evaluating the impacts of age, gender, cellular composition, and genetics on immune-related gene transcript levels and those of age, gender, smoking, and cytomegalovirus (CMV) infections on leukocyte distribution in blood. Further study might help us better understand the elements that influence immune responses and how they affect clinical outcomes.

    Study: Smoking changes adaptive immunity with persistent effects. Image Credit: NeydtStock / ShutterstockStudy: Smoking changes adaptive immunity with persistent effects. Image Credit: NeydtStock / Shutterstock

    About the study

    In the present study, researchers investigated environmental variables associated with cytokine responsiveness to immunological activation.

    The team measured the levels of several cytokines [C‐X‐C motif chemokine ligand 5 (CXCL5), colony-stimulating factor 2 (CSF2), interferon-gamma (IFNγ), interleukin-1 beta (IL-1β), IL-2, 6, 8, 10, 12p70, 13, 17, 23, and tumor necrosis factor (TNF)] after 22 hours of whole-blood stimulations with 11 immunological agonists for 1,000 Milieu Intérieur project donors and in an unstimulated (control) condition. They categorized the stimulations as microbial, viral, T-lymphocyte activated, and cytokines.

    Heat maps and principal component analyses (PCA) of 13 cytokine molecules investigated in 12 immunological stimulations revealed the individual cytokines generated by every independent condition. The team performed hierarchical clustering evaluations of log mean variations in cytokine levels to identify groups corresponding to stimulation types.

    The researchers compiled 136 environmental, socio-demographic, nutritional, and clinical variables from the digital case report forms and tested for their relationships with cytokines induced in every stimulation using likelihood ratio tests (LRTs) with age, experimental batch, and gender as covariates. They also investigated human leukocyte antigen (HLA) as a predictor of immune response variability, particularly in antigen-specific responses. The team investigated whether smoking-cytokine correlations continued when particular subsets of circulating immune cells were included in their models, as these cells are related to cytokine elevations. They evaluated the biological impact of smoking on cytokine production, calculating the effect sizes for the smoking variables in the linear models and assessing the influence of 326 soluble proteins in sera obtained from 400 donors.

    The researchers investigated whether epigenetic pathways contribute to the impact of smoking on adaptive immune responses. They analyzed deoxyribonucleic acid (DNA) methylation at more than 850,000 CpG sites and investigated whether the levels may explain the association between smoking and cytokine levels following SEB stimulation. The study was especially well-suited to identifying response protein quantitative trait loci (pQTLs) since it tested 5,699,237 high-quality imputed single nucleotide polymorphisms (SNPs) for relationships with the cytokines elicited by each stimulation.

    Results

    The team identified smoking, CMV latent infection, and body mass index (BMI) as the most significant drivers of cytokine response variability. Smoking impacts innate and adaptive immune responses, with the influence on innate responses diminishing after quitting and associated with serum carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) levels. However, the impact on adaptive responses lasts long after smoking cessation and is associated with epigenetic memory.

    The study highlighted eleven factors related to one or more cytokines in the immune stimulations, with BMI being the most prevalent. Smoking-related factors were related to interleukin-2 and interleukin-13 (adaptive immunity) in Staphylococcus aureus enterotoxin B superantigen (SEB), anti-cluster of differentiation 3 (anti-CD3) and anti-CD28 immune stimulations, and CXCL5 following Escherichia coli infections or innate immunological stimulations. The findings indicate that smoking causes inflammation and reduces immunity against bacterial infections.

    Cytomegalovirus latent infection was associated with TNF, CSF2, and IFNγ cytokines secreted by adaptive immune cells. BMI-related factors were related to CXCL5 following Bacillus Calmette-Guérin (BCG) immune stimulation, and interleukin-2 following SEB stimulation demonstrated obesity dysregulation. The team found no significant association between major histocompatibility complex (MH) class II, DQ beta 1, and HLA.DBQ1.1P, and IL-6 in the control condition.

    The study found 2,416 CpG locations related to smoking in the Milieu Intérieur sample, with 129 significantly associated with IL-2 in SEB stimulation. However, 11 CpGs abolished the relationship between smoking and IL-2 and IL-13. Current smokers had lower DNA methylation than non-smokers, but former smokers had an intermediate methylation level. The number of years smoked, total cigarettes smoked, and IL-2 levels in SEB stimulation were adversely linked with DNA methylation, although the number of years after smoking typically correlated positively.

    Overall, the study findings identified three novel factors, i.e., smoking status, CMV latent infection, and BMI, associated with variability in cytokine secretion following immunological stimulation. These characteristics may have clinical consequences for the risk of contracting infections, cancer, or autoimmune diseases. Smokers have a heightened inflammatory response after bacterial activation, which promptly decreases after quitting. However, the impacts on adaptive immunity last for years after stopping. The link between smoking and long-lived B and T cell subsets and DNA methylation offers a potential for long-term consequences in the adaptive response.

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  • A closer look reveals lasting impacts

    A closer look reveals lasting impacts

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    In a recent study published in the journal Pediatrics, a large team of scientists from the United States (U.S.) reviewed existing studies on post-acute sequelae of coronavirus disease 2019 (COVID-19) (PASC) to understand the long-term impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in the pediatric population, including factors such as prevalence, clinical characteristics, risk factors, and underlying mechanisms.

    ​STATE-OF-THE-ART REVIEW – Postacute Sequelae of SARS-CoV-2 in Children. Image Credit: Donkeyworx / Shutterstock

    Background

    The global impact of the COVID-19 pandemic has touched multiple spheres of life, with economic and social consequences apart from the massive effect on the medical and healthcare fields. Studies have shown that the pandemic has disproportionately affected specific racial and socioeconomic groups. Furthermore, a significant portion of the population continues to struggle with persistent and debilitating aftereffects and symptoms of COVID-19, which has now been called PASC or long coronavirus disease (long COVID).

    Estimates indicate that the U.S. had approximately 20% pediatric cases of COVID-19, of which 10%–20% were thought to develop into PASC, which translates to roughly 5.8 million children in the country. The present study summarizes the current understanding of the epidemiology, prevalence, underlying mechanisms, clinical characteristics, and outcomes of PASC in the pediatric population.

    PASC epidemiology

    The review found no consensus on the prevalence of PASC among children, with a 4% to 62% prevalence being reported across studies. The researchers believe that differences in factors such as study design, follow-up durations, diagnostic criteria, and study population are responsible for the wide range of prevalence estimates. Furthermore, the broad symptoms, affecting multiple organ systems, and overlaps with existing comorbidities also make it challenging to diagnose PASC.

    There is also a paucity of studies examining the trajectory of PASC in the pediatric population, with very few studies having examined the progression of the disease beyond a year. Studies found that only 15% of asymptomatic SARS-CoV-2 infections in children progress to PASC, while 45% of the symptomatic infections were found to result in long-lasting sequelae.

    Furthermore, infections with variants before the emergence of Omicron were found to increase the risk of PASC. Increasing age, severity of the infection, higher body weight, chronic underlying medical conditions, and the organ systems affected during the acute SARS-CoV-2 infection were all found to be risk factors for developing PASC.

    While the contribution of environmental and psycho-social factors in the development and manifestation of PASC has not been well investigated, the scientists believe that the escalating food and housing insecurity, disruption of educational and health care resources, and lower family income could have increased the mental and physical health problems in children, lowering immunity, and exacerbating existing illnesses.

    PASC in children

    Based on existing information, the team formulated a conceptual model for PASC in the pediatric population. They defined PASC in children as a heterogeneous group of symptoms occurring after a SARS-CoV-2 infection, consisting of persistent COVID-19 symptoms such as cough, dyspnea, fatigue, headaches, anosmia, ageusia, and chronic pain. Furthermore, exacerbation of existing conditions such as increased cough in children with asthma, deterioration of neurodevelopmental and mental health conditions, and diabetic ketoacidosis in pediatric diabetes cases are also thought to be a part of PASC.

    The review emphasizes the need to give special consideration to understanding the development of PASC in children at a higher risk of SARS-CoV-2 infections due to existing comorbidities and medical conditions. The researchers also discussed the potential development of de-novo post-acute conditions and the onset of autoimmune disorders. Studies have already reported multisystem inflammatory syndrome in children (MIS-C) as being one of the prevalent complications of COVID-19 in children.

    The review also provided a comprehensive summary of the wide range of manifestations and symptoms of PASC, including constitutional symptoms such as persistent fatigue, post-exertional malaise, brain fog or difficulty concentrating, depressive symptoms, and somnolence. The researchers also discussed the respiratory, cardiac, neurological, olfactory, gastrointestinal, mental health, musculoskeletal, dermatological, and inflammatory or hematological manifestations of PASC in detail.

    Furthermore, the study also examined the role of PASC in exacerbating underlying conditions in children, such as asthma, fibromyalgia, and connective tissue disorders, as well as post-infectious conditions such as MIS-C and de-novo conditions such as diabetes, autoimmune disorders, and neurological problems that could potentially develop during PASC.

    Conclusions

    To summarize, the review examined studies investigating the long-term consequences of SARS-CoV-2 infections in children and presented a comprehensive picture of the current understanding of PASC in children. The findings indicate that while the severity and prevalence of COVID-19 in the pediatric population were not as high as in adults, PASC does entail severe and long-lasting consequences, including the development of new autoimmune conditions and diabetes. These results highlight the need to form initiatives to further understand the susceptibility of children with underlying medical conditions to SARS-CoV-2 infections.

    Journal reference:

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  • AI’s ability to detect COVID-19 from coughs faces real-world challenges

    AI’s ability to detect COVID-19 from coughs faces real-world challenges

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    A recent Nature Machine Intelligence study investigated the efficacy of audio-based artificial intelligence (AI) classifiers in predicting severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection status. SARS-CoV-2 is the causal organism of the coronavirus disease 2019 (COVID-19) pandemic.

    Study: Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Image Credit: Aliaksandra Post / ShutterstockStudy: Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Image Credit: Aliaksandra Post / Shutterstock

    Background

    Since SARS-CoV-2 infection could cause both symptomatic and asymptomatic manifestations, it is important to develop accurate tests to avoid general population quarantine. Previous studies have revealed that AI-based classifiers trained with respiratory audio data could identify SARS-CoV-2 status. 

    Although these studies indicated the effectiveness of AI-based classifiers, many challenges surfaced while applying them in real-world settings. Some factors that withheld AI-based classifier applications were sampling biases, unvalidated data on participants’ COVID-19 status, and delay between infection and audio recording. It is imperative to determine whether the audio biomarkers of COVID-19 are unique to SARS-CoV-2 infection or are inappropriate confounding signals.

    About the Study

    The current study focussed on determining whether audio-based classifiers can be accurately used for COVID-19 screening. A large-scale polymerase chain reaction (PCR) dataset linked to audio-based COVID-19 screening (ABCS) was used. For this study, participants of the Real-time Assessment of Community Transmission (REACT) program and the National Health Service (NHS) Test-and-Trace (T+T) service were invited. All relevant demographic data was extracted from T+T/REACT records.

    Participants were asked to complete survey questions and record four audio clips. For audio recordings, they were asked to read a specific sentence, followed by three successive exhalations, making a “ha” sound. Furthermore, the participants were asked to record forced coughs once and three times in succession. All recordings were documented in .wav format. The quality of the audio recordings was assessed, and 5,157 records were removed for quality-related issues.

    Human figures represent study participants and their corresponding COVID-19 infection status, with the different colours portraying different demographic or symptomatic features. When participants are randomly split into training and test sets, the randomized split models perform well at COVID-19 detection, achieving AUCs in excess of 0.8; however, matched test set performance is seen to drop to estimated AUC between 0.60 and 0.65, with an AUC of 0.5 representing random classification. Inflated classification performance is also seen in engineered out of distribution test sets such as: the designed test set, in which a select set of demographic groups appear solely in the testing set, and the longitudinal test set, in which there is no overlap in the time of submission between train and test instances. The 95% confidence intervals calculated via the normal approximation method are shown, along with the corresponding n numbers of the train and test sets.Human figures represent study participants and their corresponding COVID-19 infection status, with the different colours portraying different demographic or symptomatic features. When participants are randomly split into training and test sets, the randomized split models perform well at COVID-19 detection, achieving AUCs in excess of 0.8; however, matched test set performance is seen to drop to estimated AUC between 0.60 and 0.65, with an AUC of 0.5 representing random classification. Inflated classification performance is also seen in engineered out of distribution test sets such as: the designed test set, in which a select set of demographic groups appear solely in the testing set, and the longitudinal test set, in which there is no overlap in the time of submission between train and test instances. The 95% confidence intervals calculated via the normal approximation method are shown, along with the corresponding n numbers of the train and test sets.

    Study Findings

    In this study, a respiratory acoustic dataset of 67,842 individuals was collected. Among them, 23,514 individuals tested positive for COVID-19. All data were linked with PCR test results. It must be noted that the most significant number of COVID-19-negative participants were recruited from six REACT rounds compared to the T+T channel.

    The dataset considered in this study exhibited promising coverage across England. No significant association between geographical location and COVID-19 status was noted. The highest level of COVID-19 imbalance was found in Cornwall. A previous study indicated recruitment bias in ABCS, particularly linked with age, language, and gender, in both training data and test sets. Despite this bias, the training dataset was balanced in accordance with age and gender across COVID-positive and COVID-negative subgroups. 

    Consistent with previous studies, the unadjusted analysis conducted in this study exhibited that AI classifiers can predict COVID-19 status with high accuracy. However, when measured confounders were matched, a weak performance of AI classifiers in detecting SARS-CoV-2 status was observed.

    Based on the findings, the current study proposed some guidelines to rectify recruitment bias’s effect for future studies. Some of the recommendations are listed below:

    1. Audio samples stored in repositories must include details of the study recruitment criteria. In addition, relevant information about the individuals, including their gender, age, time of COVID-19 test, SARS-CoV-2 symptoms, and locations, must be documented along with the audio recording.
    2. All confounding factors must be identified and matched to help control recruitment bias.
    3. Experimental design must be developed, keeping the possible bias in mind. In most cases, data matching leads to a reduction in sample size. Observational studies recruit participants focusing on the maximized possibility of matching measured confounders.
    4. The predictive values of the classifiers must be compared with standard protocol findings.
    5. AI classifiers’ predictive accuracy must be assessed. However, the predictive accuracy, sensitivity, and specificity vary depending on the targeted population.
    6. The classifiers’ utility must be assessed for each testing outcome.
    7. The replication study must be conducted in randomized cohorts. Furthermore, pilot studies must be conducted in real-world settings based on domain-specific utility.

    Conclusions

    The current study has come with limitations that include the possibility of potential unmeasured confounders across REACT and T+T recruitment channels. For instance, PCR testing for COVID-19 was performed several days after self-screening of symptoms. In contrast, PCR tests in REACT were conducted on a pre-determined date, irrespective of the onset of symptoms. Although the majority of confounders were matched, there is a possibility of the presence of residual predictive variation.

    Despite the limitations, this study highlighted the need to develop accurate machine-learning evaluation procedures to obtain unbiased outputs. Furthermore, it revealed that confounding factors are hard to detect and control across many AI applications.

    Journal reference:

    • Coppock, H. et al. (2024) Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Nature Machine Intelligence. 1-14. DOI: 10.1038/s42256-023-00773-8, https://www.nature.com/articles/s42256-023-00773-8

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  • Hunters key to early detection of zoonotic diseases, study finds

    Hunters key to early detection of zoonotic diseases, study finds

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    To prevent future health crises, monitoring the emergence of zoonotic diseases in wild meat value chains is essential. In this regard, the role of community hunters is crucial, as they can report early signs of possible disease in game animals.

    Study: An experimental game to assess hunter’s participation in zoonotic diseases surveillance. Image Credit: Virrage Images / Shutterstock.com

    Background

    Since the mid-twentieth century, zoonotic diseases have caused 60% of emerging disease events. More recently, wildlife has been suspected to be the original reservoir of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of the coronavirus disease 2019 (COVID-19) pandemic.

    Wild animal hunting and trade facilitate human-wildlife interactions and spillover events. Community-based surveillance can provide early warning and aid in limiting the spread of a zoonotic disease. However, research has shown that local communities perceive the risk of disease transmission from animals to humans differently.

    About the study

    In a recent study published in BMC Public Health, researchers designed an experimental game (EG) to better understand the response of community hunters when encountered with signs of zoonotic diseases in game animals.

    EGs provide important insights into the decision-making of a group of individuals. These “players” are confronted with hypothetical scenarios and are asked to choose among different options. Observations from EGs are compared to game theoretical predictions, which assume players to be rational utility-maximizers.

    In the forested area of Gabon in central Africa, an EG was developed and tested that mimicked the implementation of a community-based surveillance system. Voluntary reports of hunters were used to monitor zoonotic diseases in wildlife.

    Both subsistence and commercial hunters were included in the EG. The key aim was to identify the characteristics of hunters, surveillance, and epidemiological processes that could influence their probability of participating in wildlife disease surveillance.

    A total of 88 hunters were divided into nine groups, each comprising five to 13 players. Over 21 rounds of the EG were performed, each of which involved a hunting trip simulation where the payers were likely to capture a wild animal with clinical signs of zoonotic disease.

    When signs of the zoonotic disease were visible, the participants were asked to report or sell/consume the animal. Reporting meant lower hunting revenue but also a lower probability of the spread of a zoonotic disease, which could benefit the entire community.

    Key findings

    A false alert, defined as a flagged case not caused by a zoonotic disease, led to reduced case reports in the subsequent round. Concerning hunter characteristics, those who engaged in agricultural activity, in addition to hunting, flagged suspected cases more often than their counterparts. The number of potential case reports rose with each round, thus suggesting a greater inclination to report throughout the game.

    In the game-theoretic model, participation in surveillance was associated with positive externalities. Relevant information benefits the community as a whole; however, it comes at a cost for the reporting player, which could lead to sub-optimal participation in reporting. The game sessions corroborated this theoretical hypothesis.

    The subsequent reduction in reports followed by a false report was due to false reports reducing the anticipated benefit of reporting. Prior research has shown that from a societal point of view, false alerts are acceptable as long their costs do not exceed the benefits of accurate disease detection.

    In the future, community engagement programs should highlight the utility of periodic false alerts. This will help maintain regular surveillance and its proper functioning in the event a zoonotic disease emerges.

    Players engaging in agricultural work were more likely to flag suspected cases of zoonotic disease than their counterparts. For these hunters, agriculture often accounts for a significant portion of household income, thereby reducing their reliance on hunting revenue to support their families. Thus, economic dependence on wild meat likely governs the decision to participate in surveillance systems.

    Conclusions

    The current study highlights the usefulness of EGs in enhancing our understanding of hunters’ willingness to participate in zoonotic disease surveillance. Extending the game to include all potential actors of surveillance along the wild meat value chains could provide helpful information to better manage the risks stemming from zoonotic diseases.

    Journal reference:

    • Pouliquen, A., Mapeyi, G. A. B., Vanthomme, G., et al. (2024) An experimental game to assess hunter’s participation in zoonotic diseases surveillance. BMC Public Health 24(342). doi:10.1186/s12889-024-17696-7

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  • Study reveals high insomnia rates in non-hospitalized COVID-19 survivors

    Study reveals high insomnia rates in non-hospitalized COVID-19 survivors

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    In a recent study published in Frontiers in Public Health, researchers investigated insomnia prevalence and its association with anxiety and depression in the non-hospitalized coronavirus disease 2019 (COVID-19)-recovered community.

    Study: Sleep quality among non-hospitalized COVID-19 survivors: a national cross-sectional study. Image Credit: Stock-Asso/Shutterstock.com
    Study: Sleep quality among non-hospitalized COVID-19 survivors: a national cross-sectional study. Image Credit: Stock-Asso/Shutterstock.com

    Background

    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has afflicted millions globally since late 2019, with most cases resolved by mid-2023. Common symptoms include coughing, weariness, fever, dyspnea, musculoskeletal issues, gastrointestinal complaints, anosmia, dysgeusia, and vertigo. Post-infection and long-term physical and psychological difficulties are serious public health concerns.

    Insomnia is a prevalent complaint, particularly among hospitalized COVID-19 patients. High-risk variables include being female, younger, and more educated, as well as having anxiety, depression, or post-traumatic stress disorder. Poor mental health is associated with insufficient sleep, and chronic disorders such as obstructive sleep apnea (OSA) can affect glycemic control, neurocognitive impairment, and aberrant functional pulmonary alterations.

    About the study

    In the current nationwide cross-sectional study, researchers investigated insomnia prevalence among COVID-19 survivors with no or moderate symptoms who did not require hospitalization throughout the recovery period (six months) and discovered relevant variables.

    Between June and September 2022, the team conducted a web-based survey among 1,056 COVID-19-recovered individuals who recovered within six months of acute SARS-CoV-2 infection and did not need hospitalization. They used the Depression Anxiety and Stress Scale-14 (DASS-14) and the Insomnia Severity Index (ISI). They obtained data on demographics such as age, marital status, sex, educational attainment, occupation, employment status, and comorbidities.

    The team asked the respondents to rate their SARS-CoV-2 infection severity and duration (days from the initial SARS-CoV-2-positive to the initial SARS-CoV-2-negative report). In addition, the respondents compared their sleep quality, sleep initiation, and total sleep duration in the previous two weeks with the time before confirming the SARS-CoV-2 infection.

    The team used multivariate logistic regressions to determine odds ratios (OR) for the relationships between anxiety and depression scores and insomnia levels among the survey respondents. They included adult COVID-19 survivors (who recovered as confirmed using polymerase chain reaction (PCR) within six months and did not require COVID-19-associated hospitalization) in Vietnam’s general population. They excluded individuals diagnosed with insomnia or psychological disorders before the study.

    Results

    The study included 1,056 individuals, with the majority being married (64%), female (69%), and having attended university (69%). After the SARS-CoV-2 infection, almost a third of respondents reported shorter sleep duration, worsened sleep quality, and more difficulties falling asleep, and half of them reported more nocturnal awakenings. Insomnia prevalence was 76%, with 23% of patients reporting severe insomnia.

    Individuals with anxiety (OR, 3.9) or depression (OR, 3.5) had a significantly increased risk of having insomnia. Other characteristics that increased the likelihood of sleeplessness included higher educational attainment and pre-existing medical conditions, but COVID-19 duration and symptoms had no significant relationship.

    Individuals who were divorced or widowed, female, had postgraduate education, were not actively employed, or suffered from chronic medical conditions had higher mean ISI ratings than their peers. Concerning COVID-19, 92% of infected individuals experienced symptoms (mean, 11 weeks). Although these symptomatic individuals showed higher ISI scores (15.2), there was no significant difference compared to individuals without symptoms.

    The mean scores for anxiety and depression were 7.6 and 6.4, respectively, with 439 (42%) and 291 (28%) individuals reporting relevant symptoms, respectively. Individuals with symptoms of anxiety (18.7) and depression (19.1) scored significantly higher on the ISI compared to those without (12.4 and 13.5, respectively). Participants experiencing insomnia scored higher on anxiety (9.2) and depression (7.8) than the overall group mean.

    In univariate analysis, those who were wedded and had a university degree were significantly less likely to experience insomnia than single and formally-educated individuals. Students were significantly more likely to experience insomnia compared to healthcare workers. Individuals with a history of chronic medical conditions were significantly more likely to suffer from insomnia following COVID-19 compared to healthy individuals. After controlling for variables, healthcare professionals had a significantly increased likelihood of insomnia (OR, 1.6) than workers in other professions; however, there were no differences compared to those who did not work or were students.

    Conclusion

    Overall, the study findings highlighted insomnia prevalence among COVID-19 survivors, with more than 75% reporting it. This percentage is much higher than that of the general population (10% to 20%) and hospitalized survivors (12% to 47%). Individuals with chronic medical conditions are more likely to suffer from insomnia, which is underreported. Public health researchers should anticipate a greater frequency of insomnia and sleep disorders in this group, which can last for one-third of healed patients up to one year after infection.

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  • Paxlovid enhances treatment options for COVID-19 patients

    Paxlovid enhances treatment options for COVID-19 patients

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    In a recent review published in the Pharmaceutics, a group of authors explored the design, synthesis, and mechanism of action of Paxlovid, a Protease inhibitor (PI) drug combination for treating coronavirus disease 2019 (COVID-19).

    Study: The Design, Synthesis and Mechanism of Action of Paxlovid, a Protease Inhibitor Drug Combination for the Treatment of COVID-19. Image Credit: Tobias Arhelger/Shutterstock.com

    Background 

    The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, significantly challenged global healthcare systems and medical science.

    In response, researchers worldwide developed vaccines with innovative mechanisms and small-molecule antivirals targeting crucial viral proteins.

    Among these, PaxlovidTM, a blend of nirmatrelvir and ritonavir PIs, stands out for its effectiveness in treating COVID-19.

    Nirmatrelvir inhibits SARS-CoV-2’s main protease, vital for viral replication, while ritonavir boosts nirmatrelvir’s effectiveness by inhibiting Cytochrome P450 3A4 (CYP3A4), an enzyme that would otherwise degrade nirmatrelvir quickly.

    Further research is needed to develop alternative main protease (MPro) inhibitors despite the success of the nirmatrelvir-ritonavir combination, ensuring continued effectiveness against COVID-19.

    PIs as antivirals for Hepatitis C virus (HCV) and Human immunodeficiency virus (HIV) 

    PI Drugs for HCV and HIV Infections

    PIs are key in treating HCV and HIV infections. HCV, a small ribonucleic acid (RNA) virus causing hepatic diseases, is targeted by PIs like asunaporevir, telaprevir, and boceprevir, focusing on the nonstructural (NS)3/4A serine protease.

    These inhibitors are peptidomimetics, containing peptide bonds and a ‘warhead’ group that binds covalently but reversibly to the enzyme’s active site.

    HIV PIs target the virus’s aspartic acid protease, which is crucial for viral replication. They are used in antiretroviral therapy, transforming HIV from fatal to chronic.

    Development and mechanism of Nirmatrelvir

    Nirmatrelvir, developed from Pfizer’s earlier SARS-CoV-1 PI .. PF-00835231, faced challenges in oral absorption.

    Modifications like altering the warhead and substituting various molecular components enhanced its binding affinity and antiviral activity, eventually leading to nirmatrelvir with a nitrile warhead, improving solubility and synthesis.

    Despite different warheads, its structural similarity to boceprevir, and its role as a covalent inhibitor of SARS-CoV-2 Mpro makes it significant in COVID-19 treatment.

    Synthesis of nirmatrelvir

    Nirmatrelvir’s synthesis involves coupling the P1 building block and the P2-P3 dipeptide, with the final step being the formation of the nitrile warhead.

    The process starts with protected amino acid derivatives, proceeding through stages like Boc-deprotection, ester cleavage, and dipeptide formation.

    The synthesis yields nirmatrelvir with high efficiency and introduces a new approach involving a Ugi-type three-component reaction for higher diastereoselectivity.

    Synthesis and structure-activity relationship (SAR) study of nirmatrelvir analogs

    Research by Chia and co-workers led to the synthesizing nirmatrelvir analogs with different P1′ moieties, examining the role of the warhead in antiviral activity.

    These studies revealed varying levels of effectiveness in protease inhibition and antiviral activity, with some derivatives showing similar or superior effects to nirmatrelvir. However, challenges in cell penetration and specificity to SARS-CoV-2 limited the broader application of these analogs.

    Novel covalent and non-covalent inhibitors of SARS-CoV-2 Mpro

    Recent developments in SARS-CoV-2 Mpro inhibitors have introduced both peptidomimetic and non-peptidic inhibitors.

    These include warheads, such as epoxide rings and fluoromethyl groups, offering alternative mechanisms of covalent binding to the enzyme.

    Non-covalent inhibitors, like ensitrelvir, show lower reactivity but better selectivity due to their secondary interaction nature. These developments represent crucial steps in diversifying therapeutic options against COVID-19 and its evolving strains.

    Ritonavir as a pharmacokinetic enhancer

    Structure, activity, and interactions of ritonavir

    Originally an HIV protease inhibitor, Ritonavir is known for its efficacy at low doses (~100 mg) in inhibiting the CYP3A4 enzyme, a crucial element in drug metabolism.

    While high doses of Ritonavir are poorly tolerated, its low-dose effectiveness is leveraged in combination therapies with other HIV protease inhibitors, enhancing their half-lives and thus reducing required dosages.

    This unique use of Ritonavir has been explored even in early COVID-19 treatments. However, its use poses risks of significant drug–drug interactions, especially with medications metabolized by CYP3A4, potentially elevating their levels to toxic concentrations.

    Additionally, Ritonavir’s effect on other enzymes and transport proteins is noted, albeit of lesser importance in Paxlovid treatment.

    Synthesis of ritonavir

    developed at Abbott Laboratories, Ritonavir’s synthesis involves complex chemical processes, combining chiral amine and carboxylic acid building blocks.

    The synthesis starts with a cyclocondensation reaction involving thioformamide and ethyl 2-chloroacetate, followed by a series of steps leading to the formation of ritonavir.

    This intricate process involves various intermediate compounds and chemical reactions, including triethylamine and 4-dimethylaminopyridine, highlighting the sophistication required in pharmaceutical synthesis.

    The production of Ritonavir demonstrates the intricate chemical engineering necessary to develop effective pharmaceutical agents.

    Paxlovid—application and activity against mutant variants

    Paxlovid, combining nirmatrelvir and ritonavir, has shown significant efficacy in reducing COVID-19-related hospitalizations and mortality.

    While it has gained emergency use authorization in various regions, its effectiveness against emerging strains and mutant variants is under continuous scrutiny.

    The evolving landscape of SARS-CoV-2 mutations necessitates ongoing monitoring to ensure the sustained efficacy of treatments like Paxlovid.

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  • SARS-CoV-2 fragments found to mimic immune system peptides, fueling inflammation

    SARS-CoV-2 fragments found to mimic immune system peptides, fueling inflammation

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    In a recent study published in the journal Proceedings of the National Academy of Sciences, researchers analyzed the inflammatory capacity of fragmented components of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

    The intensive research during the coronavirus disease 2019 (COVID-19) pandemic has helped understand SARS-CoV-2 infection. Nevertheless, what makes the virus capable of causing a dangerous inflammatory response remains unclear. Research has suggested that amphiphilic, cationic peptides from the innate immune system undergo amyloid-like assembly with anionic nucleic acids and form proinflammatory complexes.

    Study: Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes. Image Credit: NIAIDStudy: Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes. ​​​​​​​Image Credit: NIAID

    The study and findings

    The present study investigated whether fragmented SARS-CoV-2 peptides assemble with anionic double-stranded RNA (dsRNA) into supramolecular complexes. The viral proteome was considered a reservoir of peptide fragments liberating after the proteolytic destruction of virions. The researchers leveraged a support vector machine (SVM) classifier to recognize antimicrobial peptide (AMP)-like sequences (xenoAMPs) in the SARS-CoV-2 proteome.

    Viral protein sequences were scanned via a moving window of 24–34 amino acids to identify potential xenoAMPs and test whether they behave like AMPs if cleaved at different positions. Sequences were selected based on the output provided by the classifier as a sigma (σ) score, wherein a strongly positive score implied the sequence was highly likely to be an AMP.

    Existence of exogenous mimics of pro-inflammatory host antimicrobial peptides (xenoAMPs) in SARS-CoV-2 proteins. (A) SARS-CoV-2 proteins are scanned with a machine-learning AMP classifier. Each queried sequence is given a σ score that measures its AMP-ness. Three representative high-scoring sequences are studied: xenoAMP(ORF1ab), xenoAMP(S), and xenoAMP(M). The grey bars mark the location where the corresponding sequences are selected. (B) SARS-CoV-2 sequences are aligned and compared to their homologs in a common cold human coronavirus HCoV-OC43: Control (ORF1ab), Control(S), and Control(M). Asterisks, colons, and periods indicate positions that have fully conserved residues, those that have strongly similar properties, and those that have weakly similar properties, respectively. Color is assigned to each residue using the ClustalX scheme. (C) σ score heatmaps compare the distribution of high-scoring sequences in three proteins from SARS-CoV-2 and HCoV-OC43. The first amino acid in each sequence is colored according to its average σ score; regions with negative average σ scores (non-AMPs) are colored white. “Hot spot” clusters of high-scoring sequences for SARS-CoV-2 (bright yellow regions bracketed in red boxes) have systematically higher scores and span wider regions of sequence space compared to HCoV-OC43. This trend suggests that hot spots in SARS-CoV-2 can generate higher scoring sequences for a greater diversity of enzymatic cleavage sites than those in HCoV-OC43.

    Existence of exogenous mimics of pro-inflammatory host antimicrobial peptides (xenoAMPs) in SARS-CoV-2 proteins. (A) SARS-CoV-2 proteins are scanned with a machine-learning AMP classifier. Each queried sequence is given a σ score that measures its AMP-ness. Three representative high-scoring sequences are studied: xenoAMP(ORF1ab), xenoAMP(S), and xenoAMP(M). The grey bars mark the location where the corresponding sequences are selected. (B) SARS-CoV-2 sequences are aligned and compared to their homologs in a common cold human coronavirus HCoV-OC43: Control (ORF1ab), Control(S), and Control(M). Asterisks, colons, and periods indicate positions that have fully conserved residues, those that have strongly similar properties, and those that have weakly similar properties, respectively. Color is assigned to each residue using the ClustalX scheme. (C) σ score heatmaps compare the distribution of high-scoring sequences in three proteins from SARS-CoV-2 and HCoV-OC43. The first amino acid in each sequence is colored according to its average σ score; regions with negative average σ scores (non-AMPs) are colored white. “Hot spot” clusters of high-scoring sequences for SARS-CoV-2 (bright yellow regions bracketed in red boxes) have systematically higher scores and span wider regions of sequence space compared to HCoV-OC43. This trend suggests that hot spots in SARS-CoV-2 can generate higher scoring sequences for a greater diversity of enzymatic cleavage sites than those in HCoV-OC43.

    Further, the team selected specific sequences from this population of (high-scoring) sequences with a high cationic charge. Specifically, they focused on prototypical candidates from the membrane (M) protein, spike (S) protein, and open reading frame 1ab (ORF1ab) polyprotein. In silico analyses showed that these xenoAMPs could be generated during proteasomal degradation, with matrix metalloproteinase 9 (MMP9) and neutrophil elastase (NE) capable of generating them.

    Next, the team compared SARS-CoV-2 xenoAMPs with homologous sequences from SARS-CoV-1 and non-pandemic human CoVs. This showed that sequences were partially conserved. A comparison of σ score heat maps of ORF1ab, S, and M proteins between SARS-CoV-2 and HCoV-OC43 revealed that high-scoring sequences were clustered into hotspots, with SARS-CoV-2 hotspots having higher scores and spanning wider regions than those of HCoV-OC43.

    Further, mass spectrometry was performed on tracheal aspirate samples from patients with severe COVID-19. The team detected fragments of host AMP, cathelicidin LL-37, in 20 samples (out of 29). By contrast, 28 samples contained viral peptide fragments, some of which had sufficiently high σ scores to qualify as xenoAMPs.

    The three xenoAMPs, xenoAMP(S), xenoAMP(M), and xenoAMP(ORF1ab), were experimentally observed to chaperone and assemble with dsRNA into complexes similar to LL-37. Polyinosine: polycytidylic acid (Poly(I:C) was used as a synthetic analog to mimic the viral dsRNA generated during replication. The structures of xenoAMPs-poly(I:C) complexes were cognate to host AMPs-dsRNA complexes.

    Next, the team investigated the robustness of these self-assembled proinflammatory complexes under non-optimal conditions. They found that the nanocrystalline structures were preserved when participating xenoAMPs were shortened. Besides, SARS-CoV-2 xenoAMPs were found to co-crystallize with LL-37, suggesting that host AMPs and xenoAMPs could synergistically activate inflammatory responses.

    The immune activation capacity of xenoAMPs from SARS-CoV-2 was compared with that of homolog peptides from HCoV-OC43 using human monocytes. XenoAMP-poly(I:C)-treated monocytes released 1.7-fold more interleukin (IL)-8 than poly(I:C) treated controls. By contrast, complexes formed with homologous peptides from HCoV-OC43 induced much lower IL-8 levels.

    In addition, xenoAMP-poly(I:C) stimulation of primary human dermal microvascular endothelial cells (HDMVECs) triggered robust production of IL-6, which was not observed with complexes formed from HCoV-OC43 peptides. Notably, xenoAMP-poly(I:C)-treated HDMVECs showed significant upregulation of several proinflammatory chemokine and cytokine genes.

    Finally, the researchers measured the immune activation capacity in mice. C57BL/6 mice unexposed to infection were treated with xenoAMP(ORF1ab)-poly(I:C) complexes or poly(I:C)-alone (control). XenoAMP(ORF1ab)-poly(I:C) treatment increased plasma levels of IL-6 and C-X-C motif chemokine ligand 1 (CXCL1) by 1.6 and 2.2 times, respectively, compared to poly(I:C)-alone. Moreover, IL-6 and CXCL1 levels increased 1.2 times in the lung compared to the control treatment.

    Conclusions

    In sum, the study has illustrated an unexpected mechanism of inflammation propagating through uninfected cells in COVID-19, wherein viral fragments mimic AMPs like LL-37. This could be salient to understand why the host immune system in COVID-19 resembles that of individuals with autoimmune conditions like rheumatoid arthritis and lupus.

    The researchers found that host proteases could generate xenoAMPs, suggesting that protease inhibitors suppressing xenoAMP generation could have a clinical impact on viral-induced inflammation. The proteolytic degradation of SARS-CoV-2 could differ across host individuals, possibly explaining the heterogeneity of infection outcomes, e.g., asymptomatic and fatal.

    Journal reference:

    • Zhang Y, Bharathi V, Dokoshi T, et al. Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes. Proc Natl Acad Sci USA, 2024, DOI: 10.1073/pnas.2300644120, https://www.pnas.org/doi/10.1073/pnas.2300644120

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  • Fatigue and cognitive deficits improve over two years

    Fatigue and cognitive deficits improve over two years

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    In a recent study published in the journal EClinicalMedicine, a team of scientists from Germany assessed the long-term trajectories of sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections such as cognitive deficits and fatigue and attempted to identify the risk factors that could predict non-recovery from these sequelae.

    Study: Predictors of non-recovery from fatigue and cognitive deficits after COVID-19: a prospective, longitudinal, population-based study. Image Credit: p.ill.i / ShutterstockStudy: Predictors of non-recovery from fatigue and cognitive deficits after COVID-19: a prospective, longitudinal, population-based study. Image Credit: p.ill.i / Shutterstock

    Background

    Although worldwide vaccination efforts have successfully limited the transmission and severity of SARS-CoV-2 infections and lowered the morbidity and mortality associated with the coronavirus disease 2019 (COVID-19) pandemic, long coronavirus disease (long-COVID) has emerged as a serious consequential health concern. Over 60 million COVID-19 patients are believed to suffer from long-COVID, with cognitive impairments and fatigue being the most common symptoms.

    Approximately 26% of the long-COVID patients suffer from cognitive deficits, while fatigue impacts 19% of the patients, with both symptoms significantly affecting their overall quality of life and preventing the resumption of everyday activities such as work and exercise.

    Furthermore, while electronic health records of long-COVID patients indicate that cognitive deficits are observed throughout the first two years following a SARS-CoV-2 infection, the longitudinal information on fatigue is sparse. The few existing studies are primarily on older patients with preexisting comorbidities, and the results are conflicting, making it difficult to extrapolate these findings to the general population.

    About the study

    In the present study, the researchers used data from the German National Pandemic Cohort Network to evaluate the trajectories of the two most prevalent long-COVID symptoms — cognitive deficits and fatigue — over a period of 18 months in 3,000 patients. They hypothesized that long-term follow-up would indicate a recovery from both symptoms in most patients.

    The scientists also aimed to identify the risk factors that could indicate non-recovery from cognitive deficits or fatigue following COVID-19, which could be used to predict recovery rates and make informed decisions on treating these conditions. The longitudinal, prospective, multicenter, population-based study included participants above the age of 18 years who tested positive for SARS-CoV-2 through a polymerase chain reaction (PCR) test.

    Baseline assessments were conducted six months after the first SARS-CoV-2 infection, and those with reinfections were excluded from the study. Assessments for follow-up were conducted a minimum of 18 months after the SARS-CoV-2 infection.

    All participants were required to fill out an online questionnaire about fatigue, and those with symptoms that indicated post-COVID syndrome or long-COVID were invited for on-site appointments to undergo cognitive assessments. Matched controls were selected based on the PCR test date, with 30% of the baseline participants and their matched controls being invited for in-person follow-ups.

    The FACIT-Fatigue or Functional Assessment of Chronic Illness Therapy-Fatigue scale, which assesses 13 symptoms related to fatigue on a five-point scale, was used to measure one of the primary measures. Scores below the cut-off indicated recovery from fatigue, while those above the cut-off indicated persistent fatigue. The scores were used to further characterize fatigue severity.

    The Montreal Cognitive Assessment was used to assess cognitive performance, with scores between 0 and 30 indicating severe to no cognitive deficits. Educational levels were considered while assessing these scores to account for learning deficits.

    Results

    The results showed that while cognitive deficits and fatigue were the two most prevalent long-COVID symptoms, these symptoms showed improvements over two years in close to half the patients recovering from post-COVID syndrome. Furthermore, depressive symptoms and headaches were risk factors that predicted non-recovery from fatigue in the long term, while male sex, old age, and school education levels below 12 years were predictors of non-recovery from cognitive deficits.

    Compared to the pre-COVID-19 pandemic levels of fatigue, which were around 9%, clinically relevant fatigue was reported by 21% of the participants, indicating a significant health burden due to fatigue in the post-pandemic period. However, the fatigue scores were seen to improve significantly after the follow-up period of 18 months to two years.

    Psychological distress before the SARS-CoV-2 infection was thought to be linked to the persistence of fatigue since depressive symptoms were found to be one of the significant predictors of non-recovery from fatigue. Depressive symptoms and headaches could potentially be targeted for accurate diagnosis and targeted treatment of fatigue in long-COVID patients.

    Conclusions

    To summarize, the study investigated the long-term trajectories of fatigue and cognitive impairment, the two most prevalent long-COVID symptoms, in a longitudinal cohort of long-COVID patients.

    The findings suggested that while both symptoms showed improvements over a span of two years in approximately 50% of the patients, specific risk factors such as depressive symptoms and headache predicted non-recovery from fatigue in the long term. Old age and male sex were two of the risk factors indicating non-recovery from cognitive deficits in long-COVID patients.

    Journal reference:

    • Hartung, T. J., Bahmer, T., ChaplinskayaSobol, I., Deckert, J., Endres, M., Franzpötter, K., Geritz, J., Haeusler, K. G., Hein, G., Heuschmann, P. U., Hopff, S. M., Horn, A., Keil, T., Krawczak, M., Krist, L., Lieb, W., Maetzler, C., Montellano, F. A., Morbach, C., & Neumann, C. (2024). Predictors of nonrecovery from fatigue and cognitive deficits after COVID-19: a prospective, longitudinal, population-based study. EClinicalMedicine, 69.  DOI: 10.1016/j.eclinm.2024.102456, https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(24)00035-X/fulltext

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  • HIV patients have been less vaccinated with the full initial regimen against COVID-19

    HIV patients have been less vaccinated with the full initial regimen against COVID-19

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    In December, the journal Vaccines published an analysis of COVID-19 vaccination coverage among people with HIV in Catalonia between December 2020 and July 2022. The article, resulting from a study funded by the Fundació La Marató de TV3 and led by the Centre for Epidemiological Studies on HIV/AIDS and STI of Catalonia (CEEISCAT), a group from the Germans Trias i Pujol Research Institute (IGTP), in collaboration with researchers from the PISCIS Cohort group, evaluates the primary, monovalent, and booster doses. This research aims to develop concrete action plans tailored to specific profiles to facilitate and promote vaccination.

    The study included a sample of over 200,000 individuals, 18,330 of whom have HIV and were vaccinated against COVID-19. The researchers observed a lower rate of complete primary vaccination schedule in people living with HIV (78.2%) compared to those without this condition (81.8%), with the difference being more pronounced among migrant populations. However, people living with HIV received more booster doses than the rest.

    The authors identified several factors that may contribute to the lower complete vaccination rates: having a previous diagnosis of SARS-CoV-2, the status of HIV infection, being a migrant, or having a complicated socioeconomic situation. These factors reflect barriers to vaccine access and healthcare.

    The analysis has helped identify patterns and contexts that encourage vaccination against SARS-CoV-2 among people living with HIV, as well as determining the need to improve vaccine access and address the hesitancy of vulnerable populations in taking the doses, highlighting their efficacy and safety.

    The gap widens among migrant populations

    The same group of researchers has published another article in the Open Forum Infectious Diseases journal, this time focusing on migrant individuals with HIV. The findings indicate that these individuals (over 3,000 in the sample) have undergone fewer SARS-CoV-2 tests, yet they have a similar cumulative diagnosis rate as local natives. Their vaccination rate, both in terms of the complete schedule and booster doses, is lower compared to those born in Catalonia. In contrast, there were more hospitalisations and admissions to the Intensive Care Unit (ICU) among migrants, even with similar durations of stays and mortality rates. Moreover, having two or more comorbidities in migrant individuals has been associated as a risk factor for severe COVID-19.

    The study suggests possible impediments that could justify these results, such as economic inequalities, lack of information, structural discrimination, language barriers, or distrust in the healthcare system. With this data, strategies are expected to be developed to reach the migrant population and promote vaccination, as it is crucial for protecting the individual and curbing future epidemics at a social level.

    Source:

    Germans Trias i Pujol Research Institute

    Journal reference:

    Nomah, D. K., et al. (2023). Comparative Analysis of Primary and Monovalent Booster SARS-CoV-2 Vaccination Coverage in Adults with and without HIV in Catalonia, Spain. Vaccines. doi.org/10.3390/vaccines12010044.

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